Journal article

Wavelet-based feature extraction for support vector machines for screening balance impairments in the elderly

Ahsan H Khandoker, Daniel TH Lai, Rezaul K Begg, Marimuthu Palaniswami

IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | Published : 2007

Abstract

Trip related falls are a prevalent problem in the elderly. Early identification of at-risk gait can help prevent falls and injuries. The main aim of this study was to investigate the effectiveness of a wavelet based multiscale analysis of a gait variable [minimum foot clearance (MFC)] in comparison to MFC histogram plot analysis in extracting features for developing a model using support vector machines (SVMs) for screening of balance impairments in the elderly. MFC during walking on a treadmill was recorded on 13 healthy elderly and 10 elderly with a history of tripping falls. Features extracted from MFC histogram and then multiscale exponents between successive wavelet coefficient levels a..

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